As a Software Engineer and AI researcher at my company, I was assigned to evaluate the state of the art in LLMs and agentic models. My recommendation was to adopt Claude Code. That's where the real problem started.
Two paths to orchestrate agents
I first tried to orchestrate agents deterministically using only the models. It didn't work: LLMs are probabilistic and often choose the path of least resistance instead of the correct one. The model ended up creating its own agents and skipping the ones I had defined.
Then I built a plugin for Claude with a main orchestrator, 21 subagents and 17 skills, using agent teams. It worked better, but the feature is still experimental and the bugs made it too unreliable for team use.
That's when I asked myself: what would a layer that runs deterministic prompt flows with agent orchestration, geared toward developers and dev teams, look like today? That's how AIOrc was born.
The problem it solves
At my company we have multiple projects with different stacks: a Nest.js backend with TDD, blockchain integration, fund custodians, AWS, MongoDB Atlas. A frontend with design patterns polished over years. If I wanted to use the flows my coworker had built, I had to ask them for agents, skills, context, copy them into my repo and hope Claude would follow the flow.
With AIOrc, my Claude connects to an MCP with a token. No cloning, no copying, no drift. When I migrate to Python tomorrow to add data science, I go to the public flow repository, grab what I need and use it.
A cross-disciplinary layer
We want AI to be universal. If we give Claude to a graphic designer, or if we give a backend developer who doesn't know styles the frontend flows from the team, the logic is exchanged. A developer shares the flow and the entire company — or the community — can follow their standards.
Where it stands today
Everything is oriented toward agents and automation with a clear goal: reduce execution time, gain reliability in the LLM and eliminate slop — that scattered, unreliable output models generate when they don't have a deterministic flow to follow.
It's just getting started. Today you can already create projects, orchestrate flows in compiled or server-verified mode, define eval suites that grade runs against the graph, watch live usage analytics per agent, skill and teammate, share everything with your team privately, make public what you want and consume others'. The idea is to build a community of experts in web2, web3, blockchain, Python, C# and everything else we can think of, sharing secure databases, cloud connections, interface design and software architecture.
AIOrc is still a prototype in its early steps. What it needs now are people who try it, break it and share what happened. Early feedback is what defines where it goes, and the community is what will turn it into something truly useful. If what I'm building resonates with you, join in.
Ready to start?